title: Multimodal signal processing for the analysis of cardiovascular variability.
abstract: Cardiovascular (CV) variability as a primary vital sign carrying information about CV regulation systems is reviewed by pointing out the role of the main rhythms and the various control and functional systems involved. The high complexity of the addressed phenomena fosters a multimodal approach that relies on data analysis models and deals with the ongoing interactions of many signals at a time. The importance of closed-loop identification and causal analysis is remarked upon and basic properties, application conditions and methods are recalled. The need of further integration of CV signals relevant to peripheral and systemic haemodynamics, respiratory mechanics, neural afferent and efferent pathways is also stressed.
authors.affiliation: Department of Technologies for Health, Galeazzi Orthopaedic Institute, University of Milan, 20161 Milan, Italy.
authors.forename: Alberto
authors.initials: A
authors.lastname: Porta
authors.forename: Federico
authors.initials: F
authors.lastname: Aletti
authors.forename: Frederic
authors.initials: F
authors.lastname: Vallais
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Baselli
mesh_terms: D000465:Algorithms; D002318:Cardiovascular Diseases / Q000175:diagnosis*; D003627:Data Interpretation, Statistical; D001330:Electronic Data Processing; D006439:Hemodynamics; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D008962:Models, Theoretical; D015999:Multivariate Analysis; D012815:Signal Processing, Computer-Assisted